An advanced driver assistance system (ADAS) may provide driver driving information or activate a risk alarm enabling the driver to more conveniently and safely drive a vehicle, while also allowing a driver to proactively intervene in order to prevent an accident. A typical ADAS uses a camera, a radar, a LiDAR, and the like to recognize environment and obstacles around the vehicle.
In addition to the ADAS, other assistance systems exist, such as autonomous emergency braking (AEB), a smart cruse control (SCC), a lane departure warning system (LDWS), and the like. In particular, the AEB system recognizes vehicles or pedestrians in front of a vehicle while driving to automatically perform braking before colliding therewith so as to avoid a collision or reduce collision damage. However, the existing driver assistance systems are not operated at speeds under 10 km/h and do not recognize proximity distance obstacles from the front and sides of a vehicle due to a limitation of short-range field of view (FOV) and radar reflection characteristics. Therefore, according to conventional techniques, accidents frequently occur at areas such as a spiral parking lot ramp, a narrow road, an alley, etc., as well as accidents involving pedestrians in densely populated areas.
Furthermore, conventional systems have a reduced camera recognition rate in low-light level areas, such as a parking lot. Therefore, such systems have difficulty in recognizing obstacles using the camera. Even further, the conventional systems may have trouble avoiding lateral obstacles and may not identify positions of pedestrians within/out of a vehicle width of a vehicle driving direction. Therefore, such systems may not be able to determine whether there is collision possibility.